Local feature based 3D face recognition

Yonguk Lee; Hwanjong Song; Ukil Yang; Hyungchul Shin; Kwanghoon Sohn

doi:10.1007/11527923_95

Local feature based 3D face recognition

Yonguk Lee, Hwanjong Song, Ukil Yang, Hyungchul Shin, Kwanghoon Sohn

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Conference article › peer-review

16 Citations (Scopus)

Abstract

This paper presents a 3D face recognition system based on geometrically localized facial features. We propose the feature extraction procedure using the geometrical characteristics of a face. We extract three curvatures, eight invariant facial feature points and their relative features. These features are directly applied to face recognition algorithms which are a depth-based DP (Dynamic Programming) and a feature-based SVM (Support Vector Machine). Experimental results show that face recognition rates based on the depth-based DP and the feature-based SVM are 95% for 20 people and 96% for 100 people, respectively.

Original language	English
Pages (from-to)	909-918
Number of pages	10
Journal	Lecture Notes in Computer Science
Volume	3546
DOIs	https://doi.org/10.1007/11527923_95
Publication status	Published - 2005
Event	5th International Conference on Audio - and Video-Based Biometric Person Authentication, AVBPA 2005 - Hilton Rye Town, NY, United States Duration: 2005 Jul 20 → 2005 Jul 22

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

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10.1007/11527923_95

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title = "Local feature based 3D face recognition",

abstract = "This paper presents a 3D face recognition system based on geometrically localized facial features. We propose the feature extraction procedure using the geometrical characteristics of a face. We extract three curvatures, eight invariant facial feature points and their relative features. These features are directly applied to face recognition algorithms which are a depth-based DP (Dynamic Programming) and a feature-based SVM (Support Vector Machine). Experimental results show that face recognition rates based on the depth-based DP and the feature-based SVM are 95% for 20 people and 96% for 100 people, respectively.",

author = "Yonguk Lee and Hwanjong Song and Ukil Yang and Hyungchul Shin and Kwanghoon Sohn",

year = "2005",

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pages = "909--918",

journal = "Lecture Notes in Computer Science",

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note = "5th International Conference on Audio - and Video-Based Biometric Person Authentication, AVBPA 2005 ; Conference date: 20-07-2005 Through 22-07-2005",

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TY - JOUR

T1 - Local feature based 3D face recognition

AU - Lee, Yonguk

AU - Song, Hwanjong

AU - Yang, Ukil

AU - Shin, Hyungchul

AU - Sohn, Kwanghoon

PY - 2005

Y1 - 2005

N2 - This paper presents a 3D face recognition system based on geometrically localized facial features. We propose the feature extraction procedure using the geometrical characteristics of a face. We extract three curvatures, eight invariant facial feature points and their relative features. These features are directly applied to face recognition algorithms which are a depth-based DP (Dynamic Programming) and a feature-based SVM (Support Vector Machine). Experimental results show that face recognition rates based on the depth-based DP and the feature-based SVM are 95% for 20 people and 96% for 100 people, respectively.

AB - This paper presents a 3D face recognition system based on geometrically localized facial features. We propose the feature extraction procedure using the geometrical characteristics of a face. We extract three curvatures, eight invariant facial feature points and their relative features. These features are directly applied to face recognition algorithms which are a depth-based DP (Dynamic Programming) and a feature-based SVM (Support Vector Machine). Experimental results show that face recognition rates based on the depth-based DP and the feature-based SVM are 95% for 20 people and 96% for 100 people, respectively.

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U2 - 10.1007/11527923_95

DO - 10.1007/11527923_95

M3 - Conference article

AN - SCOPUS:26444603416

SN - 0302-9743

VL - 3546

SP - 909

EP - 918

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

T2 - 5th International Conference on Audio - and Video-Based Biometric Person Authentication, AVBPA 2005

Y2 - 20 July 2005 through 22 July 2005

ER -

Local feature based 3D face recognition

Abstract

All Science Journal Classification (ASJC) codes

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